search for: popmean

Displaying 4 results from an estimated 4 matches for "popmean".

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2012 Nov 05
0
Diference in results from doBy::popMeans, multcomp::glht and contrast::contrast for a lme model
Hello R users, I'm analyzing an experiment in a balanced incomplet block design (BIB). The effect of blocks are assumed to be random, so I'm using nlme::lme for this. I'm analysing another more complex experiments and I notice some diferences from doBy::popMeans() compared multcomp::glht() and contrast::contrast(). In my example, glht() and contrast() were equal I suspect popMeans() are doing something diferent. This a proprosital difference? Does popMeans account the variance of random effects or something similar? The code below is reproducible, for eas...
2007 Aug 22
2
gWidgets (tcltk): problem extracting values from widgets in glayout grid
Hello, I haven't been able to find an example for the second case below -- or perhaps I didn't recognize it when I saw it. Is there a value for x such that svalue(x) will return "bbb", either by itself or as part of an array? Or do I need to do something else entirely? (R2.5.1; Windows XP) > #### gWidgets test > options("guiToolkit"="tcltk") >
2012 Apr 03
1
Imputing missing values using "LSmeans" (i.e., population marginal means) - advice in R?
...stand what they are, I have absolutely no idea how to a) calculate them in R and b) how to use them to impute my missing values in R. Again, I've searched the mail lists, internet and literature and have not found any documentation to advise on how to do this - I'm lost. I've looked at popMeans, but have no clue how to use this with predict() - if this is even the route to go. Any advice would be much appreciated. Note that YEAR will be treated as a factor and not a linear variable (i.e., the relationship between COUNT and YEAR is not linear - rather there are highs and lows about every...
2012 Mar 25
2
avoiding for loops
I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",